Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Jul 7.
Published in final edited form as: Subst Use Misuse. 2022 Jul 7;57(10):1581–1586. doi: 10.1080/10826084.2022.2096240

Prospective associations of tobacco weight control beliefs with e-cigarette use patterns in the PATH Study

Tyler B Mason 1,2,*, Alayna P Tackett 1,2, Afton Kechter 1,2, Adam M Leventhal 1,2
PMCID: PMC9704110  NIHMSID: NIHMS1846914  PMID: 35799480

Abstract

Introduction:

Some adolescents report using e-cigarettes (EC) for weight-related reasons, but longitudinal studies are lacking. This study examined associations between tobacco weight control beliefs and body mass index (BMI) with EC use patterns over one year.

Methods:

Data from Waves 1 and 2 (September 2013 to October 2015) of the Population Assessment of Tobacco and Health (PATH) study were used. Questions about tobacco weight control beliefs, EC use patterns (never, ever, never to current, ever to current, current to current), cigarette and other tobacco product use, demographics, and BMI were examined among adolescent respondents across Wave 1 and Wave 2.

Results:

Most adolescents were never EC users (85.8%). Prevalence of EC use patterns were low across categories of use (0.6% - 5.3%). Higher BMI was associated with transition from ever but not current use at Wave 1 to current use at Wave 2. Greater baseline tobacco weight control beliefs and increases in tobacco weight control beliefs were associated with most EC use patterns compared to never use.

Conclusions:

Greater tobacco weight control beliefs were risk factors for e-cigarette initiation and maintenance among a nationally representative sample of adolescents. BMI was minimally associated with e-cigarette use patterns. Additional studies are needed to replicate and further examine these preliminary prospective associations between weight control beliefs and EC use.

Keywords: E-cigarettes, body mass index, weight control, adolescents

E-cigarette use has increased substantially among adolescents over the past ten years (Perikleous et al., 2018), with 11.3% of United States high school students reporting past 30-day use of e-cigarettes in 2021 (Gentzke, et al., 2022). This recent increase in e-cigarette use is concerning as e-cigarettes may lead to initiation of other tobacco products and other substances and negatively affects adolescent brain development (Nicksic & Barnes, 2019; Tobore, 2019). Given the harmful effects of e-cigarette use during the adolescent developmental period, it is critical to understand factors associated with e-cigarette initiation among adolescents. Furthermore, adolescent obesity has increased in the United States in the past few decades such that 20.6% of adolescents now have obesity (Sanyaolu et al., 2019). Therefore, weight-related factors may be salient risk factors for e-cigarette initiation.

Adolescence is a key period of risk for internalization of sociocultural norms of thinness and use of unhealthy weight control behaviors (Izydorczyk & Sitnik-Warchulska, 2018; Stephen et al., 2014), and one of the purported uses of e-cigarettes by adolescents is for weight control (Morean & Wedel, 2017). Unhealthy weight control behaviors typically include self-induced vomiting, diet pills, and laxative use whereas healthy weight control behaviors involve fruit/vegetable intake, physical activity, and self-monitoring (Boutelle et al., 2002; Stephen et al., 2014). Adolescents with overweight or obesity are more likely to use unhealthy weight control behaviors compared to their normal weight counterparts (Boutelle et al., 2002; López-Guimerà et al., 2013), which may be due to elevated dieting and body image and weight concerns in adolescents with overweight and obesity (Leal et al., 2020; Vander Wal, 2012). Weight-motivated tobacco use is a longstanding phenomenon as tobacco products can suppress appetite, reduces food cravings, and increases metabolic rate (Audrain-McGovern & Benowitz, 2011; Chao et al., 2019). Unique from combustible cigarettes, e-cigarette liquids are available in a wide array of palatable flavors (e.g., candy and cookie). Thus, individuals who are motivated to lose weight and/or control appetite may attempt to use e-cigarettes to suppress appetite and satisfy cravings for unhealthy foods and drinks.

Emerging cross-sectional research has supported the association of tobacco weight control motives and expectancies with e-cigarette use in adolescents (Morean et al., 2020). In addition, adolescents with overweight or obesity, who are at elevated risk for use of unhealthy weight control methods, are more likely to report e-cigarette use than adolescents with normal weight (Green et al., 2017). Adolescents with higher BMI may be more likely to use e-cigarettes for weight control or appetite suppression (Fahey et al., 2021; Mason & Leventhal, 2021). However, research has yet to use longitudinal data to examine associations of tobacco weight control beliefs and body mass index (BMI) with e-cigarette initiation among adolescents. Given the lack of data on directionality of associations, it is unclear if e-cigarette use prevention programs for adolescents focused on weight control beliefs are warranted. The purpose of the current study was to examine associations between tobacco weight control beliefs and BMI with e-cigarette use patterns over the course of one year follow-up using nationally representative data from the longitudinal Population Assessment of Tobacco and Health (PATH) study. Baseline tobacco weight control beliefs and BMI at Wave 1 (W1) and changes in tobacco weight control beliefs between W1 and Wave 2 (W2) were tested as correlates of e-cigarette use transition patterns.

Method

Participants and Procedure

Publicly available data were used from the PATH study, an ongoing, nationally representative, longitudinal cohort study of adolescents and adults in the United States. The present analysis focused on W1 and W2, given the availability of all measures at these waves. Data collection occurred from September 2013 to October 2015. Details about survey interview procedures, questionnaires, sampling, weighting, and accessing the data are available elsewhere (National Addiction & HIV Data Archive Program, 2018). The PATH study was approved by the Westat institutional review board. Adolescent participants aged 12 to 17 years in the PATH study provided assent, and their parent or legal guardian provided consent. At W1, the weighted response rate for the household screener was 54.0%. Among households that were screened, the overall weighted response rate for the adolescent interview was 78.4% at W1 (N=13,651) and 87.3% at W2 (N=12,172). The differences in the number of completed interviews between waves reflect attrition owing to nonresponse, aging out of the sample, mortality, replenishment sampling, and other factors. The analyses in this study included participants who provided pertinent data for both waves and were younger than 18 years at W2.

Measures

E-cigarette use patterns.

The PATH study provides study derived variables of tobacco and e-cigarette user groups that already exist in the public-use data files and are published elsewhere (National Addiction & HIV Data Archive Program, 2018; Tourangeau et al., 2019). To examine transitions in use from W1 and W2, adolescent e-cigarette use was categorized into the following groups: (1) Never User, (2) W1 Ever Use Only, (3) W1 Never Use to W2 Ever Use, (4) W1 and W2 Ever Use, (5) W1 Current to W2 Ever Use, (6) W1 Never Use to W2 to Current Use, (7) W1 Current to W2 Current, and (8) W1 Ever to W2 Current Use.

BMI.

Participants self-reported their height and weight. BMI in kg/m2 was calculated using the standard formula (Garrow & Webster, 1985).

Demographic characteristics.

The PATH study provides a self-reported participant sex variable by using the household information at W1 only (male or female options only). The following categories measured self-reported participant race: White alone, Black alone, Asian alone, another (including multiracial). Participants’ ethnicity was categorized as either Hispanic or non-Hispanic. W1 study derived variables for age categories were used.

Combustible cigarette and other tobacco product use.

To represent adolescents who ever tried combustible cigarettes or other tobacco products, the PATH study derived measures of W1 and W2 ever use of combustible cigarette and other tobacco product were used. Other tobacco use included any use of cigars, cigarillos, pipe, hookah, smokeless tobacco, snus, dissolvable tobacco, bidi, and kretek.

Tobacco weight control beliefs.

The following question item was asked in W1 and W2 to assess tobacco weight control beliefs: “I think using tobacco would help me control my weight,” with the following response options: (1) Strongly agree, (2) Agree, (3) Disagree, and (4) Strongly disagree. The item was reversed scores such that higher scores indicated greater tobacco weight control belief. A change score was created by subtracting tobacco weight control belief score at W1 from W2 (i.e., change in Tobacco weight control beliefs=W2 tobacco weight control beliefs–W1 tobacco weight control beliefs).

Statistical Analyses

Analyses were conducted in SPSS v25.0 (IBM; Armonk, NY). Descriptive statistics were run. Primary analyses were calculated using the complex sampling module within SPSS, which allows for weighting of the data. The data were weighted using the PATH study provided strata, cluster, and W2 longitudinal weight variables. General linear models with complex sampling examined associations of demographic factors (i.e., sex, age, race, ethnicity, and BMI) with tobacco weight control beliefs. Univariable models were calculated to study the association between each demographic factor and baseline tobacco weight control beliefs. Then, a multivariable model was conducted to examine associations of baseline demographic variables with follow-up tobacco weight control beliefs, controlling for baseline tobacco weight control beliefs. A multinomial regression with complex sampling was used to investigate associations between baseline tobacco weight control beliefs, change in tobacco weight control beliefs from W1 to W2, and baseline standardized BMI with e-cigarette use patterns. Covariates included sex, age, race, ethnicity, ever use of combustible cigarettes at either wave, and ever use of other tobacco products at either wave.

Results

The majority of adolescents were never users (85.8%) followed by ever use at W2 only (5.3%), ever use at W1 only (2.1%), ever use at W1 and W2 (2.0%), current use at W2 only (1.7%), Current at W1 only (1.3%), Ever Use W1 Current Use W2 (1.1%), and current use at both waves (W1 and W2; 0.6%). Mean tobacco weight control beliefs at Wave 1 were 1.33 (SD=0.55), and mean tobacco weight control beliefs at W2 were 1.30 (SD=0.55). W1 and W2 tobacco weight control beliefs were only moderately correlated (r=.34, p<.001), which suggests inter-individual variability in change in tobacco weight control beliefs across W1 and W2 (mean change score=0.02, SD=0.63).

Table 1 displays associations between demographic factors and tobacco weight control beliefs at W1 and W2. Older age and higher BMI were associated with greater W1 tobacco weight control beliefs; sex, race, and ethnicity were not associated with W1 tobacco weight control beliefs. Controlling for W1 weight control beliefs, higher BMI and older age were associated with higher tobacco weight control beliefs at W2; male sex and Black race also were associated with lower tobacco weight control beliefs at W2, but mean differences were small.

Table 1.

Associations between demographic factors and tobacco weight control (WC) beliefs

M(SE) Estimate p
Univariable models of associations with baseline tobacco WC beliefs as outcome (Wave 1)
Sex
 Male 1.30 (0.01) −0.01 .63
 Female (Ref) 1.30 (0.01)
Age
 12–14 1.27 (0.01) −0.08 <.001
 15–17 (Ref) 1.35 (0.01)
Race
 Black 1.29 (0.01) −0.01 .61
 Another 1.30 (0.02) 0.01 .78
 White (Ref) 1.30 (0.01)
Ethnicity
 Hispanic 1.31 (0.01) 0.02 .19
 Non-Hispanic (Ref) 1.29 (0.01)
 Body mass index - 0.01 .001
Multivariable model of associations with tobacco WC beliefs at Wave 2 as outcome
Baseline tobacco WC beliefs - 0.36 <.001
Sex
 Male 1.30 (0.01) −0.02 .04
 Female (Ref) 1.32 (0.01)
Age
 12–14 1.27 (0.01) −0.08 <.001
 15–17 (Ref) 1.35 (0.01)
Race
 Black 1.28 (0.02) −0.06 <.001
 Another 1.32 (0.02) −0.02 .21
 White (Ref) 1.34 (0.01)
Ethnicity
 Hispanic 1.30 (0.01) −0.01 .35
 Non-Hispanic (Ref) 1.32 (0.01)
 Body mass index - 0.01 <.001
Open in a new tab

Note. Ref=reference group.

Table 2 displays associations of tobacco weight control beliefs and standardized BMI with e-cigarette use outcomes. Compared to never users, higher BMI was associated with transition from ever, but not current use at W1 to current use at W2. Except for the W1 ever use but not current use at either W2 group, greater baseline tobacco weight control beliefs were associated with all e-cigarette use patterns (i.e., ever use at W1 only, ever use at W2 only, ever use at W1 and W2, current use at W1 only, current use at Wave 2 only, and current use at W1 and W2) compared to never users at both waves. Compared to never users, increases in tobacco weight control beliefs were associated with all e-cigarette use patterns except for ever use at W1 only.

Table 2.

Multinomial Logistic Regression of Associations of Tobacco Weight Control Beliefs and BMI with E-Cigarette Use Patterns across Baseline and Follow-up

W1 Ever Use → W2 Never W1 Never → W2 Ever Use W1 and W2 Ever Use W1 Current → W2 Ever Use W1 Never → W2 Current Use W1 Current Use → W2 Current Use W1 Ever Use → W2 Current Use
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Covariates
Female vs. male 0.71 (0.49, 1.02) 0.91 (0.75, 1.12) 0.75 (0.49, 1.15) 0.65 (0.39, 1.08) 0.77 (0.53, 1.12) 0.73 (0.38, 1.42) 0.64 (0.40, 1.04)
Hispanic vs. Non-Hispanic 1.56 (1.07, 2.27) 0.94 (0.67, 1.34) 0.89 (0.56, 1.43) 1.10 (0.65, 1.87) 0.86 (0.52, 1.43) 0.65 (0.28, 1.52) 0.51 (0.28, 0.93)
15–17 years vs. 12–14 years 2.22 (1.49, 3.31) 1.68 (1.29, 2.20) 1.83 (1.15, 2.92) 4.49 (2.67, 7.55) 1.70 (1.14, 2.55) 4.30 (1.90, 9.73) 2.44 (1.26, 4.74)
Black vs. White 0.95 (0.50, 1.78) 0.50 (0.32, 0.80) 0.60 (0.30, 1.23) 1.21 (0.55, 2.70) 0.58 (0.30, 1.13) 0.32 (0.07, 1.46) 0.15 (0.04, 0.64)
Another vs. White 0.99 (0.61, 1.61) 0.74 (0.46, 1.19) 0.85 (0.54, 1.33) 1.60 (0.86, 2.99) 0.87 (0.48, 1.57) 0.93 (0.34, 2.52) 1.36 (0.72, 2.56)
Ever cigarette use 13.78 (9.46, 20.06) 7.38 (5.53, 9.84) 35.30 (21.94, 56.80) 45.37 (25.45, 80.91) 7.99 (5.00, 12.77) 34.75 (13.85, 82.23) *
Ever OTP use 0.61 (0.33, 1.11) 1.32 (0.95, 1.83) 1.27 (0.82, 1.96) 1.03 (0.54, 1.94) 1.23 (0.68, 2.23) 1.26 (0.50, 3.17) 1.17 (0.56, 2.45)
Correlates
BMI-stand 1.04 (0.89, 1.23) 1.08 (0.96, 1.22) 0.99 (0.82, 1.19) 1.03 (0.83, 1.29) 0.93 (0.74, 1.17) 1.16 (0.83, 1.62) 1.26 (1.02, 1.56)
Baseline WC beliefs 1.84 (1.27, 2.68) 2.10 (1.69, 2.62) 2.38 (1.66, 3.41) 3.15 (2.08, 4.79) 2.46 (1.63, 3.71) 4.35 (2.44, 7.76) 1.53 (0.92, 2.54)
Δ WC beliefs 0.98 (0.72, 1.34) 1.95 (1.61, 2.37) 1.60 (1.24, 2.07) 1.78 (1.16, 2.74) 2.14 (1.64, 2.79) 2.23 (1.46, 3.41) 1.45 (1.02, 2.07)
Open in a new tab

Note. Reference group for all e-cigarette groups was never used e-cigarettes..W1=Wave 1; W2=Wave 2; OR=odds ratio; CI=confidence interval; OTP=other tobacco product; BMI-stand=body mass index standardized (M=0, SD=1)

*

=ns too small to calculate odds ratio.

Discussion

This paper investigated tobacco weight control beliefs among a sample of adolescents and their associations with e-cigarette use patterns, controlling for demographics and ever combustible cigarette and other tobacco product use. Tobacco weight control beliefs were associated with most e-cigarette use patterns, such that adolescents with elevated tobacco weight control beliefs at W1 were more likely to be an ever and current users of e-cigarettes. Also, adolescents who increased in tobacco weight control beliefs from wave 1 to wave 2 showed a similar pattern. These results are consistent with other cross-sectional research implicating weight control beliefs and e-cigarette use (Morean et al., 2020). However, it is important to highlight the overall high prevalence of e-cigarette never users (85.8%). These rates are consistent with prevalence rates reported by the National Youth Tobacco Survey (NYTS; Singh et al., 2016). NYTS data from 2011 – 2015 indicate significant increases in e-cigarette use among youth (1.5% in 2011 to 16% in 2015), declined slightly to 11.3% in 2016 and 2017 (Cullen et al., 2019; Singh et al., 2016). However, in 2018 there was a significant increase in e-cigarette use among youth increasing from 11.3% to 20.8% (Cullen et al., 2019; Gentzke et al., 2019). Youth use of any nicotine during adolescence is concerning as it increases the risk for nicotine dependence, exposure to carcinogens, and other harmful compounds (e.g., toxic volatile organic chemicals) found in e-cigarettes (Rubinstein et al., 2018; Singh et al., 2020). In addition, e-cigarette use in adolescence has the potential to lead to initiation of other tobacco products and other substances (Nicksic & Barnes, 2019).

Of note, baseline tobacco weight control beliefs were associated with a 4-fold increase in being a current user at both waves, which delineates tobacco weight control beliefs as a potential maintenance factor for continued e-cigarette use. Tobacco weight control beliefs may lead to use of e-cigarettes as a weight control behavior as well as learned expectancies about the ability of e-cigarettes to reduce hunger and control food cravings, which may in turn sustain use and lead to nicotine dependence. While BMI was only marginally associated with e-cigarette use patterns, higher BMI was associated with greater tobacco weight control beliefs cross-sectionally and prospectively. Therefore, tobacco weight control beliefs may mediate the association between higher BMI and e-cigarette use.

These preliminary associations found among adolescents who report higher weight control beliefs may place certain individuals at higher risk to initiate or maintain use of e-cigarettes. Future research examining the interplay of BMI, weight control beliefs, and age of initiation of e-cigarette use are needed to expand on these preliminary associations. Additionally, e-cigarette products have changed dramatically since these data were collected (e.g., newer product types, different e-liquid flavors, nicotine salt e-liquid). Currently, the most frequently used products on the market are e-cigarette with high nicotine concentration (e.g., 50 mg/ml) and greater efficiency of nicotine delivery than previous generations of e-cigarettes (Voos et al., 2019). Further, to combat youth use of e-cigarettes, the U.S. Food and Drug Administration (FDA) has implemented several regulatory strategies including flavor restrictions in close cartridge-based e-cigarette devices and increased the legal age of tobacco purchase – including e-cigarettes – to 21 years of age, and currently the FDA has yet to permit any marketing of non-tobacco (including menthol) e-cigarette flavors (FDA, 2020; 2021; 2022). While non-tobacco flavors may play an important role in the use of e-cigarettes for weight control, nicotine is a key element of tobacco products that produces reduced appetite (Audrain-McGovern & Benowitz, 2011), it is possible that weight control beliefs and use of e-cigarettes as a weight control tool may increase among youth and young adults, regardless of flavor. As such, more longitudinal research among adolescents will be needed to better understand the mechanisms underlying weight control beliefs and e-cigarette use patterns – including nicotine strength used, flavor preferences, and how weight control beliefs may lead to sustained used of e-cigarettes (Mason et al., 2020; Morean et al., 2020).

The primary strength of this study includes use of a longitudinal population-based dataset of adolescents and provides insights about the temporal nature of weight control beliefs and e-cigarette use. Several limitations must be noted. While analyses used longitudinal data, predictive interpretations cannot be made from analyses as change in e-cigarette use from baseline to follow-up was not examined. There were several assessment limitations, including brief one-item assessment of tobacco weight control beliefs, non-specificity of weight control beliefs question (tobacco use generally rather than to e-cigarettes), and questions only asked during the first two waves of the PATH study. Further, future research should examine the role of socio-economic status, weight control beliefs, and e-cigarette patterns. The first two waves of the PATH study were conducted in 2013 and 2015, which limit the generalizability to e-cigarette products currently on the market. Additionally, the prevalence of e-cigarette use reported among adolescent in the PATH study are lower than other nationally representative studies (Boyd et al., 2020). For example, differences in 2015 national prevalence rates in PATH and another nationally representative survey Monitoring the Future (MTF) were found when comparing to estimates of youth e-cigarette use, with MTF reporting higher prevalence rates (12.4%) than PATH (6.7%; Boyd et al., 2020). Future studies which prospectively assess weight control beliefs specific to e-cigarettes and e-cigarette use behaviors are needed. Finally, this study focused on e-cigarettes given that e-cigarettes are the most widely used tobacco product among adolescents (Gentzke et al., 2022), yet recent research in young adults in the military showed that a wide array of tobacco products may be used for weight control (Fahey et al., 2021). Therefore, more research is needed on use of other tobacco products for weight control in adolescents.

Nevertheless, findings provided preliminary evidence that greater tobacco weight control beliefs and BMI are potential risk factors for e-cigarette initiation and maintenance among a nationally representative sample of adolescents. Current tobacco cessation interventions have shown low efficacy among youth (Fanshawe et al., 2017); as such, novel public health prevention and interventions are needed. Results of the current study show that tobacco prevention programs should assess for tobacco weight control beliefs and provide psychoeducation about the harms of e-cigarettes and alternatives for healthy weight control behaviors.

Funding:

This project was supported in part by grants K01DK124435 from the National Institute of Diabetes and Digestive and Kidney Diseases Award Number (NIDDK) and award number K01HL148907 (Tackett) from the National Heart, Lung, and Blood Institute at the NIH. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the Food and Drug Administration. The funding agencies had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Footnotes

Conflicts of interest: The authors have no conflicts of interest to disclose.

Data availability statement:

Data is publicly available through https://www.icpsr.umich.edu/web/NAHDAP/studies/36231.

References

  1. Audrain-McGovern J, & Benowitz NL (2011). Cigarette smoking, nicotine, and body weight. Clinical Pharmacology & Therapeutics, 90(1), 164–168. 10.1038/clpt.2011.105 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Boutelle K, Neumark-Sztainer D, Story M, & Resnick M (2002). Weight control behaviors among obese, overweight, and nonoverweight adolescents. Journal of Pediatric Psychology, 27(6), 531–540. 10.1093/jpepsy/27.6.531 [DOI] [PubMed] [Google Scholar]
  3. Boyd CJ, Veliz P, Evans-Polce RJ, Eisman AB, & McCabe SE (2020). Why are national estimates so different? a comparison of youth e-cigarette use and cigarette smoking in the MTF and PATH surveys. Journal of Studies on Alcohol and Drugs, 81(4), 497–504. doi: 10.15288/jsad.2020.81.497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Chao AM, Wadden TA, Ashare RL, Loughead J, & Schmidt HD (2019). Tobacco smoking, eating behaviors, and body weight: A review. Current Addiction Reports, 6(3), 191–199. 10.1007/s40429-019-00253-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cullen KA, Gentzke AS, Sawdey MD, Chang JT, Anic GM, Wang TW, ... & King BA (2019). E-cigarette use among youth in the United States, 2019. JAMA, 322(21), 2095–2103. doi: 10.1001/jama.2019.18387 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Fahey MC, Little MA, Klesges RC, Talcott GW, Richey PA, Mehmet K, & Krukowski RA (2021). Use of Tobacco for Weight Control across Products among Young Adults in the US Military. Substance Use & Misuse, 56(1), 153–161. 10.1080/10826084.2020.1846196 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Fanshawe TR, Halliwell W, Lindson N, Aveyard P, Livingstone-Banks J, & Hartmann-Boyce J (2017). Tobacco cessation interventions for young people. Cochrane Database of Systematic Reviews, 11(11), CD003289. 10.1002/14651858.CD003289.pub6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Food and Drug Administration (FDA). (2020, January 2). FDA finalizes enforcement policy on unauthorized flavored cartridge-based e-cigarettes that appeal to children, including fruit and mint. https://www.fda.gov/news-events/press-announcements/fda-finalizes-enforcement-policy-unauthorized-flavored-cartridge-based-e-cigarettes-appeal-children.
  9. Food and Drug Administration (FDA). (2021, September 1). Tobacco 21. https://www.fda.gov/tobacco-products/retail-sales-tobacco-products/tobacco-21
  10. Food and Drug Administration (FDA). (2022, March 24). FDA Issues Decisions on Additional E-Cigarette Products. https://www.fda.gov/news-events/press-announcements/fda-issues-decisions-additional-e-cigarette-products
  11. Garrow JS, & Webster J (1985). Quetelet’s index (W/H2) as a measure of fatness. International Journal of Obesity, 9(2), 147–153. [PubMed] [Google Scholar]
  12. Gentzke AS, Creamer M, Cullen KA, Ambrose BK, Willis G, Jamal A, & King BA (2019). Vital signs: tobacco product use among middle and high school students—United States, 2011–2018. Morbidity and Mortality Weekly Report, 68(6), 157. doi: 10.15585/mmwr.mm6806e1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gentzke AS, Wang TW, Cornelius M, Park-Lee E, Ren C, Sawdey MD, Cullen KA, Loretan C, Jamal A, & Homa DM (2022). Tobacco Product Use and Associated Factors Among Middle and High School Students – National Youth Tobacco Survey, United States, 2021. Morbidity and Mortality Weekly Report, 71(No. SS-5), 1–29. 10.15585/mmwr.ss7105a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Green VR, Silveira ML, Kimmel HL, & Conway KP (2018). Body mass index and tobacco-product use among US youth: Findings from wave 1 (2013–2014) of the Population Assessment of Tobacco and Health (PATH) Study. Addictive Behaviors, 81, 91–95. 10.1016/j.addbeh.2018.02.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Izydorczyk B, & Sitnik-Warchulska K (2018). Sociocultural appearance standards and risk factors for eating disorders in adolescents and women of various ages. Frontiers in Psychology, 9, 429. 10.3389/fpsyg.2018.00429 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Leal GVDS, Philippi ST, & Alvarenga MDS (2020). Unhealthy weight control behaviors, disordered eating, and body image dissatisfaction in adolescents from São Paulo, Brazil. Brazilian Journal of Psychiatry, 42, 264–270. 10.1590/1516-4446-2019-0437 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. López-Guimerà G, Neumark-Sztainer D, Hannan P, Fauquet J, Loth K, & Sánchez-Carracedo D (2013). Unhealthy weight-control behaviours, dieting and weight status: A cross-cultural comparison between North American and Spanish adolescents. European Eating Disorders Review, 21(4), 276–283. 10.1002/erv.2206 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Mason TB, & Leventhal AM (2021). Relations among sweet taste preference, body mass index, and use of E-cigarettes for weight control motives in young adults. Eating Behaviors, 41, 101497. 10.1016/j.eatbeh.2021.101497 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Mason TB, Tackett AP, Smith CE, & Leventhal AM (2021). Tobacco product use for weight control as an eating disorder behavior: Recommendations for future clinical and public health research. International Journal of Eating Disorders. 10.1002/eat.23651 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Morean ME, Bold KW, Kong G, Camenga DR, Simon P, Jackson A, ... & Krishnan-Sarin S (2020). High school students’ use of flavored e-cigarette e-liquids for appetite control and weight loss. Addictive Behaviors, 102, 106139. 10.1016/j.addbeh.2019.106139 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Morean ME, & Wedel AV (2017). Vaping to lose weight: Predictors of adult e-cigarette use for weight loss or control. Addictive Behaviors, 66, 55–59. doi: 10.1016/j.addbeh.2016.10.022. [DOI] [PubMed] [Google Scholar]
  22. National Addiction & HIV Data Archive Program. Population Assessment of Tobacco and Health (PATH) Study Series. 2018. Accessed April 15, 2021. https://www.icpsr.umich.edu/icpsrweb/NAHDAP/series/606
  23. Nicksic NE, & Barnes AJ (2019). Is susceptibility to E-cigarettes among youth associated with tobacco and other substance use behaviors one year later? Results from the PATH study. Preventive Medicine, 121, 109–114. doi: 10.1016/j.ypmed.2019.02.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Perikleous EP, Steiropoulos P, Paraskakis E, Constantinidis TC, & Nena E (2018). E-cigarette use among adolescents: an overview of the literature and future perspectives. Frontiers in Public Health, 86. 10.3389/fpubh.2018.00086 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Rubinstein ML, Delucchi K, Benowitz NL, & Ramo DE (2018). Adolescent exposure to toxic volatile organic chemicals from e-cigarettes. Pediatrics, 141(4), e20173557. doi: 10.1542/peds.2017-3557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Sanyaolu A, Okorie C, Qi X, Locke J, & Rehman S (2019). Childhood and adolescent obesity in the United States: a public health concern. Global Pediatric Health, 6, 2333794X19891305. 10.1177/2333794X19891305 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Singh S, Windle SB, Filion KB, Thombs BD, O’Loughlin JL, Grad R, & Eisenberg MJ (2020). E-cigarettes and youth: Patterns of use, potential harms, and recommendations. Preventive Medicine, 133, 106009. doi: 10.1016/j.ypmed.2020.106009. [DOI] [PubMed] [Google Scholar]
  28. Singh T, Arrazola RA, Corey CG, Husten CG, Neff LJ, Homa DM, & King BA (2016). Tobacco use among middle and high school students — United States, 2011–2015. Morbidity and Mortality Weekly Report, 65, 361–367. 10.15585/mmwr.mm6514a1 [DOI] [PubMed] [Google Scholar]
  29. Stephen EM, Rose JS, Kenney L, Rosselli-Navarra F, & Weissman RS (2014). Prevalence and correlates of unhealthy weight control behaviors: findings from the national longitudinal study of adolescent health. Journal of Eating Disorders, 2(1), 1–9. 10.1186/2050-2974-2-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Tobore TO (2019). On the potential harmful effects of E-Cigarettes (EC) on the developing brain: The relationship between vaping-induced oxidative stress and adolescent/young adults social maladjustment. Journal of Adolescence, 76, 202–209. 10.1016/j.adolescence.2019.09.004 [DOI] [PubMed] [Google Scholar]
  31. Vander Wal JS (2012). Unhealthy weight control behaviors among adolescents. Journal of Health Psychology, 17(1), 110–120. 10.1177/1359105311409787 [DOI] [PubMed] [Google Scholar]
  32. Voos N, Goniewicz ML, & Eissenberg T (2019). What is the nicotine delivery profile of electronic cigarettes? Expert Opinion on Drug Delivery, 16(11), 1193–1203. doi: 10.1080/17425247.2019.1665647. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data is publicly available through https://www.icpsr.umich.edu/web/NAHDAP/studies/36231.

RESOURCES